Abstract

Pseudo-invariant calibration sites (PICS) have been used for the radiometric calibration and stability monitoring of satellite optical sensors. Several stable PICS, such as those in the Sahara Desert in North Africa, were selected for the vicarious calibration of earth remote sensing satellites. However, the selection procedure of PICSs in the whole of Northwest China has not been fully explored before. This paper presents a novel technique for selecting PICS in Northwest China by combined using the coefficient of variation (CV) and the iteratively reweighted multivariate alteration detection (IR-MAD) technique. IR-MAD, which calculates the differences between two multispectral N-band images from the same scene acquired at different times, is used to identify no-change pixels (NCPs) of the scene through one image pair. The NCPs from IR-MAD using the long-term data of FY-3 visible infrared radiometer (VIRR) and aqua Moderate Resolution Imaging Spectroradiometer (MODIS) were aggregated into the contiguously stable sites. The traditional spatial uniformity and temporal stability from MODIS surface products were used to select the potential PICS. By combining the results of both methods, over thirty PICSs with a wider brightness range of the scene types were selected. To confirm and characterize these PICSs over Northwest China, Landsat operational land imager (OLI) high-spatial-resolution images were used to check the spatial uniformity of the selected site to determine the specific location and the size of these sites. Additionally, the surface spectral reflectance and bidirectional reflectance distribution function (BRDF) were obtained from the field campaign at Chaidamu Basin, 2018. To demonstrate the practical utilization and usability of these PICSs, they were employed in the multi-site top of atmosphere (TOA) reflectance simulation to validate the operational calibration performance of Aqua/MODIS and FY-3D/MERSI-II (Medium Resolution Spectral Imager II). The simulation results showed good consistency compared with the observations from both MODIS and MERSI-II, with a relative bias and root mean square error (RMSE) of <5% and <0.05%, respectively. These sites provide prospects for multi-site vicarious calibrations of solar reflective bands, which may help to evaluate or characterize instrumental nonlinear responses using a wider signal dynamic from the sites in different seasons.

Highlights

  • The on-orbit calibration of space-borne earth observation instruments is required for accurate remote sensing of Earth’s environmental parameters

  • By comparing the measured reflectance spectral at 12:00 (BJT) for Xiaochaidamuhu_west and Shidaoban with Dunhuang endorsed by the Committee on Earth Observation Satellites (CEOS) Working Group on Cal/Val (WGCV), we found that the brightness of Xiaochaidamuhu_west was higher than Dunhuang above 500 nm, and Shidaoban was lower than Dunhuang below 1500 nm, which was higher than Dunhuang

  • This study carried out a full investigation of the overall potential Pseudo-invariant calibration sites (PICS) in Northwest China to meet the requirements of site vicarious calibrations for the increasing number of Chinese remote-sensing satellites

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Summary

Introduction

The on-orbit calibration of space-borne earth observation instruments is required for accurate remote sensing of Earth’s environmental parameters. The Committee on Earth Observation Satellites (CEOS) endorsed six of these North-African and Middle-Eastern as standard reference sites for the post-launch calibration of space-based optical imaging sensors. These sites are Libya 4, Mauritania 1, Mauritania 2, Algeria 3, Libya 1, and Algeria 5, which have 3% or less spatial variability, in addition to 3% or less of temporal variability across all RSBs. Using five Landsat images from 1984 to 2011, Helder et al developed an algorithm for locating optimal sites that are spatially and temporally stable [9]. This allows for multiple imaging opportunities in a place of typical PICS imaging and, increases the temporal resolution to aid in quicker identification of changes in sensor responses

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